Blog Archives

Implementing an EM Algorithm for Probit Regressions

September 30, 2014
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Implementing an EM Algorithm for Probit Regressions

Users new to the Rcpp family of functionality are often impressed with the performance gains that can be realized, but struggle to see how to approach their own computational problems. Many of the most impressive performance gains are demonstrated with seemingly advanced statistical methods, advanced C++–related constructs, or both. Even when users are able to understand how various demonstrated features operate in isolation, examples...

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Using RcppArmadillo with bigmemory

July 24, 2014
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Using RcppArmadillo with bigmemory

The bigmemory package allows users to create matrices that are external to R, stored either in RAM or on disk, allowing them to be bigger than the system RAM, and allowing them to be shared across R sessions. While these objects are defined by the big.matrix class in R, they are really just wrappers that point to external memory. The actual objects are implemented...

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Computing an Inner Product with RcppParallel

July 14, 2014
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Computing an Inner Product with RcppParallel

The RcppParallel package includes high level functions for doing parallel programming with Rcpp. For example, the parallelReduce function can be used aggreggate values from a set of inputs in parallel. This article describes using RcppParallel to parallelize the inner-product example previously posted to the Rcpp Gallery. Serial Version First the serial version of computing the inner product. For this we use a...

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Parallel Distance Matrix Calculation with RcppParallel

July 14, 2014
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Parallel Distance Matrix Calculation with RcppParallel

The RcppParallel package includes high level functions for doing parallel programming with Rcpp. For example, the parallelFor function can be used to convert the work of a standard serial “for” loop into a parallel one. This article describes using RcppParallel to compute pairwise distances for each row in an input data matrix and return an n x n lower-triangular distance matrix which...

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Summing a Vector in Parallel with RcppParallel

June 28, 2014
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Summing a Vector in Parallel with RcppParallel

The RcppParallel package includes high level functions for doing parallel programming with Rcpp. For example, the parallelReduce function can be used aggreggate values from a set of inputs in parallel. This article describes using RcppParallel to sum an R vector. Serial Version First a serial version of computing the sum of a vector. For this we use a simple call to the STL std::accumulate function: #include...

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Transforming a Matrix in Parallel using RcppParallel

June 28, 2014
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Transforming a Matrix in Parallel using RcppParallel

The RcppParallel package includes high level functions for doing parallel programming with Rcpp. For example, the parallelFor function can be used to convert the work of a standard serial “for” loop into a parallel one. This article describes using RcppParallel to transform an R matrix in parallel. Serial Version First a serial version of the matrix transformation. We take the square root of each...

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Speed Chain Ladder Analysis with Rcpp

June 23, 2014
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Speed Chain Ladder Analysis with Rcpp

The Chain Ladder method is an actuarial technique used for projecting incurred insurance claims to their ultimate loss values. The data exists as claims triangles where the claims for each accounting year increments down the rows and the claims for eac...

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Call Python from R through Rcpp

April 5, 2014
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Call Python from R through Rcpp

Introduction This post provides a brief introduction to calling Python from R through Rcpp. The official Python documentation explains how to embed python into C/C++ applications. Moreover, the Boost.Python library provides seamless interoperability between C++ and the Python programming language. Similarlly, Rcpp provides interoperability between C++ and R. Therefore, it is not hard to call Python from R through Rcpp and Boost.Python. Although there...

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Using iterators for sparse vectors and matrices

March 31, 2014
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Using iterators for sparse vectors and matrices

Iterating over a sparse vector Consider the following vector: idx1 <- c(2L, 0L, 4L, 0L, 7L) A sparse representation of this vector will tell that at entries 1,3,5 (or at entries 0,2,4 if we are 0-based) we will find the values 2,4,7. Using Eigen via RcppEigen we can obtain the coercion with .sparseView(). We can iterate over all elements (including the zeros) in a sparse vector...

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A simple array class with specialized linear algebra routines

March 20, 2014
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A simple array class with specialized linear algebra routines

Currie, Durban and Eilers write: Data with an array structure are common in statistics, and the design or regression matrix for analysis of such data can often be written as a Kronecker product. Factorial designs, contingency tables and smoothing of data on multidimensional grids are three such general classes of data and models. In such a setting, we develop an arithmetic...

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